Overview

Dataset statistics

Number of variables23
Number of observations3616
Missing cells6282
Missing cells (%)7.6%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory625.2 KiB
Average record size in memory177.0 B

Variable types

Numeric5
Text6
Categorical6
Boolean5
Unsupported1

Alerts

Pharmacy_open_to_public_ has constant value ""Constant
Fuel_Station_open_to_public_ has constant value ""Constant
Online_grocery_pickup has constant value ""Constant
objectid is highly overall correlated with businessunit_type_descriptionHigh correlation
businessunit_number is highly overall correlated with bu_num and 2 other fieldsHigh correlation
bu_num is highly overall correlated with businessunit_number and 2 other fieldsHigh correlation
businessunit_banner_description is highly overall correlated with businessunit_number and 2 other fieldsHigh correlation
businessunit_type_description is highly overall correlated with objectid and 3 other fieldsHigh correlation
businessunit_isstoreopen is highly overall correlated with businessunit_status_codeHigh correlation
businessunit_status_code is highly overall correlated with businessunit_isstoreopenHigh correlation
Grocery_delivery_status is highly overall correlated with Online_grocery_pickup_statusHigh correlation
Online_grocery_pickup_status is highly overall correlated with Grocery_delivery_statusHigh correlation
businessunit_banner_description is highly imbalanced (55.3%)Imbalance
businessunit_isstoreopen is highly imbalanced (97.0%)Imbalance
businessunit_status_code is highly imbalanced (55.5%)Imbalance
op_status is highly imbalanced (99.0%)Imbalance
Modified_Operating_Hours_ has 3616 (100.0%) missing valuesMissing
Grocery_delivery_service has 285 (7.9%) missing valuesMissing
Grocery_delivery_status has 1466 (40.5%) missing valuesMissing
Online_grocery_pickup_status has 915 (25.3%) missing valuesMissing
X has unique valuesUnique
objectid has unique valuesUnique
businessunit_number has unique valuesUnique
bu_num has unique valuesUnique
Modified_Operating_Hours_ is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2023-10-22 10:06:48.549054
Analysis finished2023-10-22 10:06:54.622671
Duration6.07 seconds
Software versionydata-profiling vv4.6.0
Download configurationconfig.json

Variables

X
Real number (ℝ)

UNIQUE 

Distinct3616
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-91.717028
Minimum-159.36503
Maximum-65.807268
Zeros0
Zeros (%)0.0%
Negative3616
Negative (%)100.0%
Memory size28.4 KiB
2023-10-22T12:06:54.745497image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Quantile statistics

Minimum-159.36503
5-th percentile-119.75631
Q1-97.333506
median-88.603161
Q3-81.707137
95-th percentile-74.572568
Maximum-65.807268
Range93.557757
Interquartile range (IQR)15.626369

Descriptive statistics

Standard deviation13.812807
Coefficient of variation (CV)-0.15060243
Kurtosis1.2294653
Mean-91.717028
Median Absolute Deviation (MAD)7.7241095
Skewness-1.0507789
Sum-331648.77
Variance190.79364
MonotonicityNot monotonic
2023-10-22T12:06:54.961180image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
-94.149054 1
 
< 0.1%
-83.470749 1
 
< 0.1%
-80.963031 1
 
< 0.1%
-77.306007 1
 
< 0.1%
-122.983962 1
 
< 0.1%
-80.332788 1
 
< 0.1%
-97.464612 1
 
< 0.1%
-82.924041 1
 
< 0.1%
-119.359391 1
 
< 0.1%
-79.091184 1
 
< 0.1%
Other values (3606) 3606
99.7%
ValueCountFrequency (%)
-159.365025 1
< 0.1%
-158.034591 1
< 0.1%
-158.005571 1
< 0.1%
-157.978362 1
< 0.1%
-157.974452 1
< 0.1%
-157.843233 1
< 0.1%
-157.842705 1
< 0.1%
-156.454892 1
< 0.1%
-155.990922 1
< 0.1%
-151.225228 1
< 0.1%
ValueCountFrequency (%)
-65.807268 1
< 0.1%
-65.889641 1
< 0.1%
-65.995746 1
< 0.1%
-65.997031 1
< 0.1%
-66.020899 1
< 0.1%
-66.076049 1
< 0.1%
-66.087612 1
< 0.1%
-66.134127 1
< 0.1%
-66.162658 1
< 0.1%
-66.627869 1
< 0.1%

Y
Real number (ℝ)

Distinct3615
Distinct (%)> 99.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean36.549835
Minimum17.993681
Maximum64.856378
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size28.4 KiB
2023-10-22T12:06:55.193385image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Quantile statistics

Minimum17.993681
5-th percentile28.121938
Q133.001415
median36.177085
Q340.39249
95-th percentile44.777001
Maximum64.856378
Range46.862697
Interquartile range (IQR)7.3910745

Descriptive statistics

Standard deviation5.1954421
Coefficient of variation (CV)0.1421468
Kurtosis0.64804047
Mean36.549835
Median Absolute Deviation (MAD)3.6345995
Skewness0.015021111
Sum132164.2
Variance26.992619
MonotonicityNot monotonic
2023-10-22T12:06:55.410785image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
41.473938 2
 
0.1%
36.3313 1
 
< 0.1%
40.659918 1
 
< 0.1%
34.944223 1
 
< 0.1%
35.580506 1
 
< 0.1%
46.153048 1
 
< 0.1%
25.746027 1
 
< 0.1%
37.695454 1
 
< 0.1%
40.111341 1
 
< 0.1%
35.604033 1
 
< 0.1%
Other values (3605) 3605
99.7%
ValueCountFrequency (%)
17.993681 1
< 0.1%
17.99736 1
< 0.1%
18.122626 1
< 0.1%
18.141237 1
< 0.1%
18.243301 1
< 0.1%
18.249254 1
< 0.1%
18.380526 1
< 0.1%
18.393823 1
< 0.1%
18.394134 1
< 0.1%
18.411224 1
< 0.1%
ValueCountFrequency (%)
64.856378 1
< 0.1%
61.309037 1
< 0.1%
61.211988 1
< 0.1%
61.192239 1
< 0.1%
61.140195 1
< 0.1%
60.564278 1
< 0.1%
55.375474 1
< 0.1%
48.818547 1
< 0.1%
48.801658 1
< 0.1%
48.554783 1
< 0.1%

objectid
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct3616
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean32379.427
Minimum29040
Maximum36706
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size28.4 KiB
2023-10-22T12:06:55.613211image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Quantile statistics

Minimum29040
5-th percentile29357.75
Q130462.5
median32084
Q334209.25
95-th percentile36290
Maximum36706
Range7666
Interquartile range (IQR)3746.75

Descriptive statistics

Standard deviation2177.0878
Coefficient of variation (CV)0.06723676
Kurtosis-1.0862057
Mean32379.427
Median Absolute Deviation (MAD)1868.5
Skewness0.29154817
Sum1.1708401 × 108
Variance4739711.2
MonotonicityStrictly increasing
2023-10-22T12:06:55.842426image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
29040 1
 
< 0.1%
33535 1
 
< 0.1%
33487 1
 
< 0.1%
33489 1
 
< 0.1%
33491 1
 
< 0.1%
33492 1
 
< 0.1%
33493 1
 
< 0.1%
33495 1
 
< 0.1%
33497 1
 
< 0.1%
33498 1
 
< 0.1%
Other values (3606) 3606
99.7%
ValueCountFrequency (%)
29040 1
< 0.1%
29045 1
< 0.1%
29046 1
< 0.1%
29047 1
< 0.1%
29048 1
< 0.1%
29049 1
< 0.1%
29050 1
< 0.1%
29053 1
< 0.1%
29056 1
< 0.1%
29057 1
< 0.1%
ValueCountFrequency (%)
36706 1
< 0.1%
36705 1
< 0.1%
36704 1
< 0.1%
36702 1
< 0.1%
36700 1
< 0.1%
36698 1
< 0.1%
36695 1
< 0.1%
36693 1
< 0.1%
36690 1
< 0.1%
36688 1
< 0.1%
Distinct3385
Distinct (%)93.6%
Missing0
Missing (%)0.0%
Memory size28.4 KiB
2023-10-22T12:06:56.186970image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Length

Max length42
Median length32
Mean length13.925608
Min length6

Characters and Unicode

Total characters50355
Distinct characters70
Distinct categories9 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3189 ?
Unique (%)88.2%

Sample

1st rowROGERS, AR
2nd rowPONCE-PR
3rd rowBROWNSVILLE TX
4th rowLAVALE, MD
5th rowPUEBLO, CO
ValueCountFrequency (%)
tx 391
 
4.3%
fl 241
 
2.7%
ca 219
 
2.4%
nc 141
 
1.6%
ga 134
 
1.5%
la 122
 
1.3%
oh 117
 
1.3%
il 117
 
1.3%
tn 113
 
1.2%
pa 108
 
1.2%
Other values (2521) 7353
81.2%
2023-10-22T12:06:56.920127image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5446
 
10.8%
A 4351
 
8.6%
N 3504
 
7.0%
E 3470
 
6.9%
L 3333
 
6.6%
O 3184
 
6.3%
I 2599
 
5.2%
R 2539
 
5.0%
T 2487
 
4.9%
S 2401
 
4.8%
Other values (60) 17041
33.8%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 41311
82.0%
Space Separator 5446
 
10.8%
Other Punctuation 1835
 
3.6%
Lowercase Letter 587
 
1.2%
Close Punctuation 489
 
1.0%
Open Punctuation 489
 
1.0%
Decimal Number 154
 
0.3%
Dash Punctuation 43
 
0.1%
Modifier Symbol 1
 
< 0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
A 4351
 
10.5%
N 3504
 
8.5%
E 3470
 
8.4%
L 3333
 
8.1%
O 3184
 
7.7%
I 2599
 
6.3%
R 2539
 
6.1%
T 2487
 
6.0%
S 2401
 
5.8%
C 1768
 
4.3%
Other values (16) 11675
28.3%
Lowercase Letter
ValueCountFrequency (%)
a 71
12.1%
e 64
10.9%
o 60
10.2%
r 53
9.0%
n 51
8.7%
l 48
 
8.2%
s 33
 
5.6%
t 30
 
5.1%
i 28
 
4.8%
d 23
 
3.9%
Other values (14) 126
21.5%
Decimal Number
ValueCountFrequency (%)
1 54
35.1%
2 29
18.8%
0 20
 
13.0%
3 11
 
7.1%
7 10
 
6.5%
6 8
 
5.2%
5 8
 
5.2%
4 8
 
5.2%
8 5
 
3.2%
9 1
 
0.6%
Other Punctuation
ValueCountFrequency (%)
, 1718
93.6%
. 59
 
3.2%
/ 29
 
1.6%
& 26
 
1.4%
' 3
 
0.2%
Space Separator
ValueCountFrequency (%)
5446
100.0%
Close Punctuation
ValueCountFrequency (%)
) 489
100.0%
Open Punctuation
ValueCountFrequency (%)
( 489
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 43
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 41898
83.2%
Common 8457
 
16.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
A 4351
 
10.4%
N 3504
 
8.4%
E 3470
 
8.3%
L 3333
 
8.0%
O 3184
 
7.6%
I 2599
 
6.2%
R 2539
 
6.1%
T 2487
 
5.9%
S 2401
 
5.7%
C 1768
 
4.2%
Other values (40) 12262
29.3%
Common
ValueCountFrequency (%)
5446
64.4%
, 1718
 
20.3%
) 489
 
5.8%
( 489
 
5.8%
. 59
 
0.7%
1 54
 
0.6%
- 43
 
0.5%
/ 29
 
0.3%
2 29
 
0.3%
& 26
 
0.3%
Other values (10) 75
 
0.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 50355
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5446
 
10.8%
A 4351
 
8.6%
N 3504
 
7.0%
E 3470
 
6.9%
L 3333
 
6.6%
O 3184
 
6.3%
I 2599
 
5.2%
R 2539
 
5.0%
T 2487
 
4.9%
S 2401
 
4.8%
Other values (60) 17041
33.8%

businessunit_number
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct3616
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3149.1341
Minimum1
Maximum9894
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size28.4 KiB
2023-10-22T12:06:57.138341image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile272.75
Q11329.5
median2732.5
Q34871.25
95-th percentile6938
Maximum9894
Range9893
Interquartile range (IQR)3541.75

Descriptive statistics

Standard deviation2164.8546
Coefficient of variation (CV)0.6874444
Kurtosis-0.69570333
Mean3149.1341
Median Absolute Deviation (MAD)1681.5
Skewness0.51084009
Sum11387269
Variance4686595.5
MonotonicityNot monotonic
2023-10-22T12:06:57.383115image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
< 0.1%
5893 1
 
< 0.1%
585 1
 
< 0.1%
5851 1
 
< 0.1%
5853 1
 
< 0.1%
5854 1
 
< 0.1%
5855 1
 
< 0.1%
5857 1
 
< 0.1%
5859 1
 
< 0.1%
586 1
 
< 0.1%
Other values (3606) 3606
99.7%
ValueCountFrequency (%)
1 1
< 0.1%
3 1
< 0.1%
4 1
< 0.1%
5 1
< 0.1%
8 1
< 0.1%
12 1
< 0.1%
14 1
< 0.1%
17 1
< 0.1%
18 1
< 0.1%
19 1
< 0.1%
ValueCountFrequency (%)
9894 1
< 0.1%
8331 1
< 0.1%
8299 1
< 0.1%
8298 1
< 0.1%
8297 1
< 0.1%
8295 1
< 0.1%
8294 1
< 0.1%
8293 1
< 0.1%
8292 1
< 0.1%
8290 1
< 0.1%

businessunit_banner_description
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct8
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size28.4 KiB
WM Supercenter
2555 
Sam's Club
436 
Neighborhood Market
377 
Wal-Mart
 
242
Walmart Fuel Station
 
3
Other values (3)
 
3

Length

Max length26
Median length14
Mean length13.649889
Min length8

Characters and Unicode

Total characters49358
Distinct characters42
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)0.1%

Sample

1st rowWM Supercenter
2nd rowWM Supercenter
3rd rowWM Supercenter
4th rowWM Supercenter
5th rowWM Supercenter

Common Values

ValueCountFrequency (%)
WM Supercenter 2555
70.7%
Sam's Club 436
 
12.1%
Neighborhood Market 377
 
10.4%
Wal-Mart 242
 
6.7%
Walmart Fuel Station 3
 
0.1%
WM On Campus/RX Facilities 1
 
< 0.1%
WM ONLINE PICKUP/DELIVERY 1
 
< 0.1%
STAND ALONE PICKUP 1
 
< 0.1%

Length

2023-10-22T12:06:57.601815image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-10-22T12:06:57.796767image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
ValueCountFrequency (%)
wm 2557
36.5%
supercenter 2555
36.5%
sam's 436
 
6.2%
club 436
 
6.2%
neighborhood 377
 
5.4%
market 377
 
5.4%
wal-mart 242
 
3.5%
fuel 3
 
< 0.1%
station 3
 
< 0.1%
walmart 3
 
< 0.1%
Other values (8) 8
 
0.1%

Most occurring characters

ValueCountFrequency (%)
e 8423
17.1%
r 6109
12.4%
3381
 
6.8%
t 3184
 
6.5%
M 3176
 
6.4%
S 2995
 
6.1%
u 2995
 
6.1%
W 2802
 
5.7%
n 2559
 
5.2%
p 2556
 
5.2%
Other values (32) 11178
22.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 35468
71.9%
Uppercase Letter 9829
 
19.9%
Space Separator 3381
 
6.8%
Other Punctuation 438
 
0.9%
Dash Punctuation 242
 
0.5%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
M 3176
32.3%
S 2995
30.5%
W 2802
28.5%
C 439
 
4.5%
N 381
 
3.9%
F 4
 
< 0.1%
I 4
 
< 0.1%
E 4
 
< 0.1%
P 4
 
< 0.1%
O 3
 
< 0.1%
Other values (10) 17
 
0.2%
Lowercase Letter
ValueCountFrequency (%)
e 8423
23.7%
r 6109
17.2%
t 3184
 
9.0%
u 2995
 
8.4%
n 2559
 
7.2%
p 2556
 
7.2%
c 2556
 
7.2%
a 1308
 
3.7%
o 1134
 
3.2%
b 813
 
2.3%
Other values (8) 3831
10.8%
Other Punctuation
ValueCountFrequency (%)
' 436
99.5%
/ 2
 
0.5%
Space Separator
ValueCountFrequency (%)
3381
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 242
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 45297
91.8%
Common 4061
 
8.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 8423
18.6%
r 6109
13.5%
t 3184
 
7.0%
M 3176
 
7.0%
S 2995
 
6.6%
u 2995
 
6.6%
W 2802
 
6.2%
n 2559
 
5.6%
p 2556
 
5.6%
c 2556
 
5.6%
Other values (28) 7942
17.5%
Common
ValueCountFrequency (%)
3381
83.3%
' 436
 
10.7%
- 242
 
6.0%
/ 2
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 49358
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 8423
17.1%
r 6109
12.4%
3381
 
6.8%
t 3184
 
6.5%
M 3176
 
6.4%
S 2995
 
6.1%
u 2995
 
6.1%
W 2802
 
5.7%
n 2559
 
5.2%
p 2556
 
5.2%
Other values (32) 11178
22.6%

businessunit_type_description
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size28.4 KiB
Retail
3180 
Wholesale
436 

Length

Max length9
Median length6
Mean length6.3617257
Min length6

Characters and Unicode

Total characters23004
Distinct characters10
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowRetail
2nd rowRetail
3rd rowRetail
4th rowRetail
5th rowRetail

Common Values

ValueCountFrequency (%)
Retail 3180
87.9%
Wholesale 436
 
12.1%

Length

2023-10-22T12:06:58.009536image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-10-22T12:06:58.167830image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
ValueCountFrequency (%)
retail 3180
87.9%
wholesale 436
 
12.1%

Most occurring characters

ValueCountFrequency (%)
e 4052
17.6%
l 4052
17.6%
a 3616
15.7%
R 3180
13.8%
t 3180
13.8%
i 3180
13.8%
W 436
 
1.9%
h 436
 
1.9%
o 436
 
1.9%
s 436
 
1.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 19388
84.3%
Uppercase Letter 3616
 
15.7%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 4052
20.9%
l 4052
20.9%
a 3616
18.7%
t 3180
16.4%
i 3180
16.4%
h 436
 
2.2%
o 436
 
2.2%
s 436
 
2.2%
Uppercase Letter
ValueCountFrequency (%)
R 3180
87.9%
W 436
 
12.1%

Most occurring scripts

ValueCountFrequency (%)
Latin 23004
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 4052
17.6%
l 4052
17.6%
a 3616
15.7%
R 3180
13.8%
t 3180
13.8%
i 3180
13.8%
W 436
 
1.9%
h 436
 
1.9%
o 436
 
1.9%
s 436
 
1.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 23004
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 4052
17.6%
l 4052
17.6%
a 3616
15.7%
R 3180
13.8%
t 3180
13.8%
i 3180
13.8%
W 436
 
1.9%
h 436
 
1.9%
o 436
 
1.9%
s 436
 
1.9%

businessunit_isstoreopen
Boolean

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size3.7 KiB
True
3605 
False
 
11
ValueCountFrequency (%)
True 3605
99.7%
False 11
 
0.3%
2023-10-22T12:06:58.302770image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
Distinct3609
Distinct (%)99.8%
Missing0
Missing (%)0.0%
Memory size28.4 KiB
2023-10-22T12:06:58.623226image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Length

Max length41
Median length34
Mean length17.716261
Min length9

Characters and Unicode

Total characters64062
Distinct characters52
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3604 ?
Unique (%)99.7%

Sample

1st row2110 W WALNUT ST
2nd row3305 AVE.BARAMAYA SUITE 100
3rd row2721 BOCA CHICA BLVD
4th row12500 COUNTRY CLUB MALL RD
5th row4080 W NORTHERN AVE
ValueCountFrequency (%)
rd 691
 
5.1%
st 549
 
4.0%
ave 410
 
3.0%
blvd 410
 
3.0%
dr 378
 
2.8%
s 368
 
2.7%
n 344
 
2.5%
e 335
 
2.5%
w 334
 
2.5%
highway 243
 
1.8%
Other values (4419) 9500
70.0%
2023-10-22T12:06:59.220829image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
9946
 
15.5%
E 3857
 
6.0%
R 3403
 
5.3%
A 3336
 
5.2%
0 3130
 
4.9%
1 2875
 
4.5%
S 2655
 
4.1%
N 2584
 
4.0%
T 2454
 
3.8%
L 2390
 
3.7%
Other values (42) 27432
42.8%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 38821
60.6%
Decimal Number 15194
 
23.7%
Space Separator 9946
 
15.5%
Other Punctuation 72
 
0.1%
Dash Punctuation 19
 
< 0.1%
Lowercase Letter 10
 
< 0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
E 3857
 
9.9%
R 3403
 
8.8%
A 3336
 
8.6%
S 2655
 
6.8%
N 2584
 
6.7%
T 2454
 
6.3%
L 2390
 
6.2%
D 2387
 
6.1%
O 2064
 
5.3%
I 1886
 
4.9%
Other values (17) 11805
30.4%
Decimal Number
ValueCountFrequency (%)
0 3130
20.6%
1 2875
18.9%
5 1779
11.7%
2 1762
11.6%
3 1313
8.6%
4 1104
 
7.3%
7 876
 
5.8%
6 863
 
5.7%
9 748
 
4.9%
8 744
 
4.9%
Lowercase Letter
ValueCountFrequency (%)
y 2
20.0%
d 2
20.0%
k 1
10.0%
w 1
10.0%
c 1
10.0%
a 1
10.0%
m 1
10.0%
e 1
10.0%
Other Punctuation
ValueCountFrequency (%)
. 66
91.7%
, 2
 
2.8%
# 2
 
2.8%
/ 1
 
1.4%
' 1
 
1.4%
Space Separator
ValueCountFrequency (%)
9946
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 19
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 38831
60.6%
Common 25231
39.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
E 3857
 
9.9%
R 3403
 
8.8%
A 3336
 
8.6%
S 2655
 
6.8%
N 2584
 
6.7%
T 2454
 
6.3%
L 2390
 
6.2%
D 2387
 
6.1%
O 2064
 
5.3%
I 1886
 
4.9%
Other values (25) 11815
30.4%
Common
ValueCountFrequency (%)
9946
39.4%
0 3130
 
12.4%
1 2875
 
11.4%
5 1779
 
7.1%
2 1762
 
7.0%
3 1313
 
5.2%
4 1104
 
4.4%
7 876
 
3.5%
6 863
 
3.4%
9 748
 
3.0%
Other values (7) 835
 
3.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 64061
> 99.9%
None 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
9946
 
15.5%
E 3857
 
6.0%
R 3403
 
5.3%
A 3336
 
5.2%
0 3130
 
4.9%
1 2875
 
4.5%
S 2655
 
4.1%
N 2584
 
4.0%
T 2454
 
3.8%
L 2390
 
3.7%
Other values (41) 27431
42.8%
None
ValueCountFrequency (%)
Ñ 1
100.0%
Distinct2073
Distinct (%)57.3%
Missing0
Missing (%)0.0%
Memory size28.4 KiB
2023-10-22T12:06:59.532330image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Length

Max length21
Median length18
Mean length8.8279867
Min length3

Characters and Unicode

Total characters31922
Distinct characters28
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1453 ?
Unique (%)40.2%

Sample

1st rowROGERS
2nd rowPONCE
3rd rowBROWNSVILLE
4th rowLAVALE
5th rowPUEBLO
ValueCountFrequency (%)
city 102
 
2.2%
san 48
 
1.1%
springs 45
 
1.0%
beach 42
 
0.9%
north 34
 
0.7%
fort 33
 
0.7%
west 29
 
0.6%
lake 29
 
0.6%
las 28
 
0.6%
saint 27
 
0.6%
Other values (1999) 4117
90.8%
2023-10-22T12:07:00.037116image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
A 3056
 
9.6%
E 3018
 
9.5%
O 2618
 
8.2%
L 2564
 
8.0%
N 2526
 
7.9%
R 2226
 
7.0%
I 2027
 
6.3%
S 1883
 
5.9%
T 1739
 
5.4%
C 1076
 
3.4%
Other values (18) 9189
28.8%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 31003
97.1%
Space Separator 918
 
2.9%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
A 3056
 
9.9%
E 3018
 
9.7%
O 2618
 
8.4%
L 2564
 
8.3%
N 2526
 
8.1%
R 2226
 
7.2%
I 2027
 
6.5%
S 1883
 
6.1%
T 1739
 
5.6%
C 1076
 
3.5%
Other values (16) 8270
26.7%
Space Separator
ValueCountFrequency (%)
918
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 31003
97.1%
Common 919
 
2.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
A 3056
 
9.9%
E 3018
 
9.7%
O 2618
 
8.4%
L 2564
 
8.3%
N 2526
 
8.1%
R 2226
 
7.2%
I 2027
 
6.5%
S 1883
 
6.1%
T 1739
 
5.6%
C 1076
 
3.5%
Other values (16) 8270
26.7%
Common
ValueCountFrequency (%)
918
99.9%
- 1
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 31922
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
A 3056
 
9.6%
E 3018
 
9.5%
O 2618
 
8.2%
L 2564
 
8.0%
N 2526
 
7.9%
R 2226
 
7.0%
I 2027
 
6.3%
S 1883
 
5.9%
T 1739
 
5.4%
C 1076
 
3.4%
Other values (18) 9189
28.8%
Distinct1034
Distinct (%)28.6%
Missing0
Missing (%)0.0%
Memory size28.4 KiB
2023-10-22T12:07:00.346043image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Length

Max length28
Median length25
Mean length7.3653208
Min length3

Characters and Unicode

Total characters26633
Distinct characters36
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique493 ?
Unique (%)13.6%

Sample

1st rowBENTON
2nd rowPONCE
3rd rowCAMERON
4th rowALLEGANY
5th rowPUEBLO
ValueCountFrequency (%)
st 66
 
1.6%
san 50
 
1.2%
orange 46
 
1.1%
jefferson 45
 
1.1%
washington 43
 
1.1%
maricopa 41
 
1.0%
dallas 40
 
1.0%
harris 37
 
0.9%
clark 36
 
0.9%
city 35
 
0.9%
Other values (1051) 3596
89.1%
2023-10-22T12:07:00.878449image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
A 3043
11.4%
E 2492
 
9.4%
O 2228
 
8.4%
N 2179
 
8.2%
R 1969
 
7.4%
L 1809
 
6.8%
S 1614
 
6.1%
I 1454
 
5.5%
T 1253
 
4.7%
C 995
 
3.7%
Other values (26) 7597
28.5%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 26123
98.1%
Space Separator 420
 
1.6%
Other Punctuation 70
 
0.3%
Dash Punctuation 13
 
< 0.1%
Lowercase Letter 7
 
< 0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
A 3043
11.6%
E 2492
 
9.5%
O 2228
 
8.5%
N 2179
 
8.3%
R 1969
 
7.5%
L 1809
 
6.9%
S 1614
 
6.2%
I 1454
 
5.6%
T 1253
 
4.8%
C 995
 
3.8%
Other values (16) 7087
27.1%
Lowercase Letter
ValueCountFrequency (%)
e 2
28.6%
a 1
14.3%
w 1
14.3%
r 1
14.3%
n 1
14.3%
c 1
14.3%
Other Punctuation
ValueCountFrequency (%)
. 66
94.3%
' 4
 
5.7%
Space Separator
ValueCountFrequency (%)
420
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 13
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 26130
98.1%
Common 503
 
1.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
A 3043
11.6%
E 2492
 
9.5%
O 2228
 
8.5%
N 2179
 
8.3%
R 1969
 
7.5%
L 1809
 
6.9%
S 1614
 
6.2%
I 1454
 
5.6%
T 1253
 
4.8%
C 995
 
3.8%
Other values (22) 7094
27.1%
Common
ValueCountFrequency (%)
420
83.5%
. 66
 
13.1%
- 13
 
2.6%
' 4
 
0.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 26633
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
A 3043
11.4%
E 2492
 
9.4%
O 2228
 
8.4%
N 2179
 
8.2%
R 1969
 
7.4%
L 1809
 
6.8%
S 1614
 
6.1%
I 1454
 
5.5%
T 1253
 
4.7%
C 995
 
3.7%
Other values (26) 7597
28.5%
Distinct52
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size28.4 KiB
2023-10-22T12:07:01.086839image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters7232
Distinct characters24
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowAR
2nd rowPR
3rd rowTX
4th rowMD
5th rowCO
ValueCountFrequency (%)
tx 400
 
11.1%
fl 250
 
6.9%
ca 222
 
6.1%
nc 145
 
4.0%
ga 135
 
3.7%
oh 120
 
3.3%
il 120
 
3.3%
tn 116
 
3.2%
va 110
 
3.0%
pa 109
 
3.0%
Other values (42) 1889
52.2%
2023-10-22T12:07:01.469496image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
A 1082
15.0%
N 663
 
9.2%
T 585
 
8.1%
L 574
 
7.9%
C 556
 
7.7%
M 475
 
6.6%
O 440
 
6.1%
I 430
 
5.9%
X 400
 
5.5%
F 250
 
3.5%
Other values (14) 1777
24.6%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 7232
100.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
A 1082
15.0%
N 663
 
9.2%
T 585
 
8.1%
L 574
 
7.9%
C 556
 
7.7%
M 475
 
6.6%
O 440
 
6.1%
I 430
 
5.9%
X 400
 
5.5%
F 250
 
3.5%
Other values (14) 1777
24.6%

Most occurring scripts

ValueCountFrequency (%)
Latin 7232
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
A 1082
15.0%
N 663
 
9.2%
T 585
 
8.1%
L 574
 
7.9%
C 556
 
7.7%
M 475
 
6.6%
O 440
 
6.1%
I 430
 
5.9%
X 400
 
5.5%
F 250
 
3.5%
Other values (14) 1777
24.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 7232
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
A 1082
15.0%
N 663
 
9.2%
T 585
 
8.1%
L 574
 
7.9%
C 556
 
7.7%
M 475
 
6.6%
O 440
 
6.1%
I 430
 
5.9%
X 400
 
5.5%
F 250
 
3.5%
Other values (14) 1777
24.6%
Distinct3572
Distinct (%)98.8%
Missing0
Missing (%)0.0%
Memory size28.4 KiB
2023-10-22T12:07:01.807404image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters36160
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3528 ?
Unique (%)97.6%

Sample

1st row72756-3246
2nd row00728-0000
3rd row78521-3501
4th row21502-7553
5th row81005-3503
ValueCountFrequency (%)
27407-2600 2
 
0.1%
39402-8854 2
 
0.1%
23602-4311 2
 
0.1%
37923-3115 2
 
0.1%
29910-7621 2
 
0.1%
70058-3405 2
 
0.1%
21801-2143 2
 
0.1%
63303-3526 2
 
0.1%
51501-7672 2
 
0.1%
29621-1344 2
 
0.1%
Other values (3562) 3596
99.4%
2023-10-22T12:07:02.387532image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 4738
13.1%
1 3758
10.4%
3 3650
10.1%
2 3631
10.0%
- 3616
10.0%
4 3171
8.8%
7 3036
8.4%
5 3025
8.4%
6 2802
7.7%
8 2496
6.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 32544
90.0%
Dash Punctuation 3616
 
10.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4738
14.6%
1 3758
11.5%
3 3650
11.2%
2 3631
11.2%
4 3171
9.7%
7 3036
9.3%
5 3025
9.3%
6 2802
8.6%
8 2496
7.7%
9 2237
6.9%
Dash Punctuation
ValueCountFrequency (%)
- 3616
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 36160
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4738
13.1%
1 3758
10.4%
3 3650
10.1%
2 3631
10.0%
- 3616
10.0%
4 3171
8.8%
7 3036
8.4%
5 3025
8.4%
6 2802
7.7%
8 2496
6.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 36160
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4738
13.1%
1 3758
10.4%
3 3650
10.1%
2 3631
10.0%
- 3616
10.0%
4 3171
8.8%
7 3036
8.4%
5 3025
8.4%
6 2802
7.7%
8 2496
6.9%

businessunit_status_code
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size28.4 KiB
5
1857 
2
1746 
6
 
11
4
 
1
3
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters3616
Distinct characters5
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)0.1%

Sample

1st row5
2nd row5
3rd row5
4th row5
5th row5

Common Values

ValueCountFrequency (%)
5 1857
51.4%
2 1746
48.3%
6 11
 
0.3%
4 1
 
< 0.1%
3 1
 
< 0.1%

Length

2023-10-22T12:07:02.587659image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-10-22T12:07:02.748970image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
ValueCountFrequency (%)
5 1857
51.4%
2 1746
48.3%
6 11
 
0.3%
4 1
 
< 0.1%
3 1
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
5 1857
51.4%
2 1746
48.3%
6 11
 
0.3%
4 1
 
< 0.1%
3 1
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3616
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 1857
51.4%
2 1746
48.3%
6 11
 
0.3%
4 1
 
< 0.1%
3 1
 
< 0.1%

Most occurring scripts

ValueCountFrequency (%)
Common 3616
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 1857
51.4%
2 1746
48.3%
6 11
 
0.3%
4 1
 
< 0.1%
3 1
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3616
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 1857
51.4%
2 1746
48.3%
6 11
 
0.3%
4 1
 
< 0.1%
3 1
 
< 0.1%

op_status
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size28.4 KiB
Open
3613 
Closed
 
3

Length

Max length6
Median length4
Mean length4.0016593
Min length4

Characters and Unicode

Total characters14470
Distinct characters9
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowOpen
2nd rowOpen
3rd rowOpen
4th rowOpen
5th rowOpen

Common Values

ValueCountFrequency (%)
Open 3613
99.9%
Closed 3
 
0.1%

Length

2023-10-22T12:07:02.943990image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-10-22T12:07:03.108855image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
ValueCountFrequency (%)
open 3613
99.9%
closed 3
 
0.1%

Most occurring characters

ValueCountFrequency (%)
e 3616
25.0%
O 3613
25.0%
p 3613
25.0%
n 3613
25.0%
C 3
 
< 0.1%
l 3
 
< 0.1%
o 3
 
< 0.1%
s 3
 
< 0.1%
d 3
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 10854
75.0%
Uppercase Letter 3616
 
25.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 3616
33.3%
p 3613
33.3%
n 3613
33.3%
l 3
 
< 0.1%
o 3
 
< 0.1%
s 3
 
< 0.1%
d 3
 
< 0.1%
Uppercase Letter
ValueCountFrequency (%)
O 3613
99.9%
C 3
 
0.1%

Most occurring scripts

ValueCountFrequency (%)
Latin 14470
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 3616
25.0%
O 3613
25.0%
p 3613
25.0%
n 3613
25.0%
C 3
 
< 0.1%
l 3
 
< 0.1%
o 3
 
< 0.1%
s 3
 
< 0.1%
d 3
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 14470
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 3616
25.0%
O 3613
25.0%
p 3613
25.0%
n 3613
25.0%
C 3
 
< 0.1%
l 3
 
< 0.1%
o 3
 
< 0.1%
s 3
 
< 0.1%
d 3
 
< 0.1%

Modified_Operating_Hours_
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3616
Missing (%)100.0%
Memory size28.4 KiB

Pharmacy_open_to_public_
Boolean

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size3.7 KiB
True
3616 
ValueCountFrequency (%)
True 3616
100.0%
2023-10-22T12:07:03.235067image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size3.7 KiB
True
3616 
ValueCountFrequency (%)
True 3616
100.0%
2023-10-22T12:07:03.357127image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

bu_num
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct3616
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3149.1341
Minimum1
Maximum9894
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size28.4 KiB
2023-10-22T12:07:03.548411image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile272.75
Q11329.5
median2732.5
Q34871.25
95-th percentile6938
Maximum9894
Range9893
Interquartile range (IQR)3541.75

Descriptive statistics

Standard deviation2164.8546
Coefficient of variation (CV)0.6874444
Kurtosis-0.69570333
Mean3149.1341
Median Absolute Deviation (MAD)1681.5
Skewness0.51084009
Sum11387269
Variance4686595.5
MonotonicityNot monotonic
2023-10-22T12:07:03.805531image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
< 0.1%
5893 1
 
< 0.1%
585 1
 
< 0.1%
5851 1
 
< 0.1%
5853 1
 
< 0.1%
5854 1
 
< 0.1%
5855 1
 
< 0.1%
5857 1
 
< 0.1%
5859 1
 
< 0.1%
586 1
 
< 0.1%
Other values (3606) 3606
99.7%
ValueCountFrequency (%)
1 1
< 0.1%
3 1
< 0.1%
4 1
< 0.1%
5 1
< 0.1%
8 1
< 0.1%
12 1
< 0.1%
14 1
< 0.1%
17 1
< 0.1%
18 1
< 0.1%
19 1
< 0.1%
ValueCountFrequency (%)
9894 1
< 0.1%
8331 1
< 0.1%
8299 1
< 0.1%
8298 1
< 0.1%
8297 1
< 0.1%
8295 1
< 0.1%
8294 1
< 0.1%
8293 1
< 0.1%
8292 1
< 0.1%
8290 1
< 0.1%

Grocery_delivery_service
Boolean

MISSING 

Distinct2
Distinct (%)0.1%
Missing285
Missing (%)7.9%
Memory size7.2 KiB
False
1738 
True
1593 
(Missing)
285 
ValueCountFrequency (%)
False 1738
48.1%
True 1593
44.1%
(Missing) 285
 
7.9%
2023-10-22T12:07:03.980401image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Grocery_delivery_status
Categorical

HIGH CORRELATION  MISSING 

Distinct2
Distinct (%)0.1%
Missing1466
Missing (%)40.5%
Memory size28.4 KiB
Available
1874 
Not Available
276 

Length

Max length13
Median length9
Mean length9.5134884
Min length9

Characters and Unicode

Total characters20454
Distinct characters11
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowAvailable
2nd rowAvailable
3rd rowAvailable
4th rowAvailable
5th rowAvailable

Common Values

ValueCountFrequency (%)
Available 1874
51.8%
Not Available 276
 
7.6%
(Missing) 1466
40.5%

Length

2023-10-22T12:07:04.154895image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-10-22T12:07:04.325718image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
ValueCountFrequency (%)
available 2150
88.6%
not 276
 
11.4%

Most occurring characters

ValueCountFrequency (%)
a 4300
21.0%
l 4300
21.0%
A 2150
10.5%
v 2150
10.5%
i 2150
10.5%
b 2150
10.5%
e 2150
10.5%
N 276
 
1.3%
o 276
 
1.3%
t 276
 
1.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 17752
86.8%
Uppercase Letter 2426
 
11.9%
Space Separator 276
 
1.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 4300
24.2%
l 4300
24.2%
v 2150
12.1%
i 2150
12.1%
b 2150
12.1%
e 2150
12.1%
o 276
 
1.6%
t 276
 
1.6%
Uppercase Letter
ValueCountFrequency (%)
A 2150
88.6%
N 276
 
11.4%
Space Separator
ValueCountFrequency (%)
276
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 20178
98.7%
Common 276
 
1.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 4300
21.3%
l 4300
21.3%
A 2150
10.7%
v 2150
10.7%
i 2150
10.7%
b 2150
10.7%
e 2150
10.7%
N 276
 
1.4%
o 276
 
1.4%
t 276
 
1.4%
Common
ValueCountFrequency (%)
276
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 20454
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 4300
21.0%
l 4300
21.0%
A 2150
10.5%
v 2150
10.5%
i 2150
10.5%
b 2150
10.5%
e 2150
10.5%
N 276
 
1.3%
o 276
 
1.3%
t 276
 
1.3%

Online_grocery_pickup
Boolean

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size3.7 KiB
True
3616 
ValueCountFrequency (%)
True 3616
100.0%
2023-10-22T12:07:04.464028image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Online_grocery_pickup_status
Categorical

HIGH CORRELATION  MISSING 

Distinct2
Distinct (%)0.1%
Missing915
Missing (%)25.3%
Memory size28.4 KiB
Available
2361 
Not Available
340 

Length

Max length13
Median length9
Mean length9.5035172
Min length9

Characters and Unicode

Total characters25669
Distinct characters11
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNot Available
2nd rowAvailable
3rd rowAvailable
4th rowAvailable
5th rowAvailable

Common Values

ValueCountFrequency (%)
Available 2361
65.3%
Not Available 340
 
9.4%
(Missing) 915
 
25.3%

Length

2023-10-22T12:07:04.633445image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-10-22T12:07:04.790549image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
ValueCountFrequency (%)
available 2701
88.8%
not 340
 
11.2%

Most occurring characters

ValueCountFrequency (%)
a 5402
21.0%
l 5402
21.0%
A 2701
10.5%
v 2701
10.5%
i 2701
10.5%
b 2701
10.5%
e 2701
10.5%
N 340
 
1.3%
o 340
 
1.3%
t 340
 
1.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 22288
86.8%
Uppercase Letter 3041
 
11.8%
Space Separator 340
 
1.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 5402
24.2%
l 5402
24.2%
v 2701
12.1%
i 2701
12.1%
b 2701
12.1%
e 2701
12.1%
o 340
 
1.5%
t 340
 
1.5%
Uppercase Letter
ValueCountFrequency (%)
A 2701
88.8%
N 340
 
11.2%
Space Separator
ValueCountFrequency (%)
340
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 25329
98.7%
Common 340
 
1.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 5402
21.3%
l 5402
21.3%
A 2701
10.7%
v 2701
10.7%
i 2701
10.7%
b 2701
10.7%
e 2701
10.7%
N 340
 
1.3%
o 340
 
1.3%
t 340
 
1.3%
Common
ValueCountFrequency (%)
340
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 25669
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 5402
21.0%
l 5402
21.0%
A 2701
10.5%
v 2701
10.5%
i 2701
10.5%
b 2701
10.5%
e 2701
10.5%
N 340
 
1.3%
o 340
 
1.3%
t 340
 
1.3%

Interactions

2023-10-22T12:06:52.920647image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-10-22T12:06:49.860743image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-10-22T12:06:50.535022image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-10-22T12:06:51.355345image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-10-22T12:06:52.164897image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-10-22T12:06:53.055662image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-10-22T12:06:49.989968image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-10-22T12:06:50.692853image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-10-22T12:06:51.505905image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-10-22T12:06:52.296987image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-10-22T12:06:53.191456image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-10-22T12:06:50.117291image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-10-22T12:06:50.817393image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-10-22T12:06:51.651237image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-10-22T12:06:52.442508image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-10-22T12:06:53.349600image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-10-22T12:06:50.269788image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-10-22T12:06:51.078413image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-10-22T12:06:51.842044image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-10-22T12:06:52.604580image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-10-22T12:06:53.492580image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-10-22T12:06:50.403570image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-10-22T12:06:51.211200image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-10-22T12:06:52.007302image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
2023-10-22T12:06:52.749335image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/

Correlations

2023-10-22T12:07:05.019835image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
XYobjectidbusinessunit_numberbu_numbusinessunit_banner_descriptionbusinessunit_type_descriptionbusinessunit_isstoreopenbusinessunit_status_codeop_statusGrocery_delivery_serviceGrocery_delivery_statusOnline_grocery_pickup_status
X1.0000.093-0.0540.0260.0260.1210.0420.0440.0880.0000.0750.0710.048
Y0.0931.000-0.1770.0420.0420.0920.0630.0360.0370.0000.0860.0000.000
objectid-0.054-0.1771.0000.4670.4670.2170.5090.0210.2730.0510.0620.0000.000
businessunit_number0.0260.0420.4671.0001.0000.5110.8060.0170.3850.0000.1300.0000.000
bu_num0.0260.0420.4671.0001.0000.5110.8060.0170.3850.0000.1300.0000.000
businessunit_banner_description0.1210.0920.2170.5110.5111.0000.9990.2990.2610.0000.1750.0430.032
businessunit_type_description0.0420.0630.5090.8060.8060.9991.0000.0000.0450.0000.1730.0120.000
businessunit_isstoreopen0.0440.0360.0210.0170.0170.2990.0001.0001.0000.0000.0000.0000.000
businessunit_status_code0.0880.0370.2730.3850.3850.2610.0451.0001.0000.0000.0000.0000.000
op_status0.0000.0000.0510.0000.0000.0000.0000.0000.0001.0000.0000.0000.000
Grocery_delivery_service0.0750.0860.0620.1300.1300.1750.1730.0000.0000.0001.0000.3150.251
Grocery_delivery_status0.0710.0000.0000.0000.0000.0430.0120.0000.0000.0000.3151.0000.905
Online_grocery_pickup_status0.0480.0000.0000.0000.0000.0320.0000.0000.0000.0000.2510.9051.000

Missing values

2023-10-22T12:06:53.759994image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
A simple visualization of nullity by column.
2023-10-22T12:06:54.256652image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2023-10-22T12:06:54.527912image/svg+xmlMatplotlib v3.7.3, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

XYobjectidbusinessunit_namebusinessunit_numberbusinessunit_banner_descriptionbusinessunit_type_descriptionbusinessunit_isstoreopenfacilitydetails_location_locatifacilitydetails_location_loca_1facilitydetails_location_loca_2facilitydetails_location_loca_3facilitydetails_location_loca_8businessunit_status_codeop_statusModified_Operating_Hours_Pharmacy_open_to_public_Fuel_Station_open_to_public_bu_numGrocery_delivery_serviceGrocery_delivery_statusOnline_grocery_pickupOnline_grocery_pickup_status
0-94.14905436.33130029040ROGERS, AR1WM SupercenterRetailTrue2110 W WALNUT STROGERSBENTONAR72756-32465OpenNaNYY1YesNaNYesNot Available
1-66.64257817.99736029045PONCE-PR2026WM SupercenterRetailTrue3305 AVE.BARAMAYA SUITE 100PONCEPONCEPR00728-00005OpenNaNYY2026NaNNaNYesNaN
2-97.47700325.92514229046BROWNSVILLE TX1000WM SupercenterRetailTrue2721 BOCA CHICA BLVDBROWNSVILLECAMERONTX78521-35015OpenNaNYY1000YesNaNYesAvailable
3-78.83505239.62490329047LAVALE, MD2027WM SupercenterRetailTrue12500 COUNTRY CLUB MALL RDLAVALEALLEGANYMD21502-75535OpenNaNYY2027YesAvailableYesAvailable
4-104.66489838.23231629048PUEBLO, CO1001WM SupercenterRetailTrue4080 W NORTHERN AVEPUEBLOPUEBLOCO81005-35035OpenNaNYY1001YesAvailableYesAvailable
5-117.45533933.93707129049RIVERSIDE (S), CA2028WM SupercenterRetailTrue5200 VAN BUREN BLVDRIVERSIDERIVERSIDECA92503-25445OpenNaNYY2028NoNaNYesNaN
6-87.13070839.03587729050LINTON IN1002WM SupercenterRetailTrue2251 E STATE HIGHWAY 54LINTONGREENEIN47441-94985OpenNaNYY1002YesNaNYesNaN
7-93.07274339.76788829053BROOKFIELD MO203WM SupercenterRetailTrue937 PARK CIRCLE DRBROOKFIELDLINNMO64628-79205OpenNaNYY203NoNaNYesNaN
8-92.47964442.70163129056WAVERLY IA1005WM SupercenterRetailTrue2700 4TH ST SWWAVERLYBREMERIA50677-43515OpenNaNYY1005YesAvailableYesAvailable
9-122.06730837.60471529057UNION CITY, CA2031Wal-MartRetailTrue30600 DYER STUNION CITYALAMEDACA94587-17172OpenNaNYY2031YesNaNYesNaN
XYobjectidbusinessunit_namebusinessunit_numberbusinessunit_banner_descriptionbusinessunit_type_descriptionbusinessunit_isstoreopenfacilitydetails_location_locatifacilitydetails_location_loca_1facilitydetails_location_loca_2facilitydetails_location_loca_3facilitydetails_location_loca_8businessunit_status_codeop_statusModified_Operating_Hours_Pharmacy_open_to_public_Fuel_Station_open_to_public_bu_numGrocery_delivery_serviceGrocery_delivery_statusOnline_grocery_pickupOnline_grocery_pickup_status
3606-82.45571829.06330936688DUNNELLON FL960WM SupercenterRetailTrue11012 NO. WILLIAMS STDUNNELLONMARIONFL34432-83105OpenNaNYY960YesAvailableYesAvailable
3607-90.49828530.07471636690LAPLACE LA961WM SupercenterRetailTrue1616 W AIRLINE HWYLA PLACEST. JOHN THE BAPTIST PARISHLA70068-33315OpenNaNYY961NoAvailableYesAvailable
3608-104.52327537.13872836693TRINIDAD CO962WM SupercenterRetailTrue2921 TOUPAL DRTRINIDADLAS ANIMASCO81082-87405OpenNaNYY962YesAvailableYesAvailable
3609-97.79486232.73149336695WEATHERFORD TX963WM SupercenterRetailTrue1836 S MAIN STWEATHERFORDPARKERTX76086-55065OpenNaNYY963NoAvailableYesAvailable
3610-106.31159631.68289836698EL PASO (S) TX964WM SupercenterRetailTrue9441 ALAMEDA AVEEL PASOEL PASOTX79907-56015OpenNaNYY964YesAvailableYesAvailable
3611-90.50857744.02102436700TOMAH WI965WM SupercenterRetailTrue222 W MCCOY BLVDTOMAHMONROEWI54660-32915OpenNaNYY965NoNaNYesNaN
3612-108.56199437.34656836702CORTEZ CO966WM SupercenterRetailTrue1835 E MAIN STCORTEZMONTEZUMACO81321-30375OpenNaNYY966YesNaNYesNaN
3613-82.63121828.45839736704SPRINGHILL / BROOKSVILLE967WM SupercenterRetailTrue1485 COMMERCIAL WAYSPRING HILLHERNANDOFL34606-45255OpenNaNYY967YesAvailableYesAvailable
3614-81.72225128.00665136705WINTER HAVEN FL968WM SupercenterRetailTrue355 CYPRESS GARDENS BLVDWINTER HAVENPOLKFL33880-44525OpenNaNYY968YesAvailableYesAvailable
3615-89.08869730.42322436706GULFPORT MS969WM SupercenterRetailTrue9350 HIGHWAY 49GULFPORTHARRISONMS39503-42135OpenNaNYY969NoNot AvailableYesAvailable